Comprehensive Molecular Characterization of Chinese Patients with Glioma by Extensive Next-Generation Sequencing Panel Analysis

Comparative genomic landscape of lower-grade glioma and glioblastoma

Biomarkers for classifying and grading gliomas have been extensively explored, whereas populations in public databases were mostly Western/European. Based on public databases cannot accurately represent Chinese population. To identify molecular characteristics associated with clinical outcomes of lower-grade glioma (LGG) and glioblastoma (GBM) in the Chinese population, we performed whole-exome sequencing (WES) in 16 LGG and 35 GBM tumor tissues. TP53 (36/51), TERT (31/51), ATRX (16/51), EFGLAM (14/51), and IDH1 (13/51) were the most common genes harboring mutations. IDH1 mutation (c.G395A; p.R132H) was significantly enriched in LGG, whereas PCDHGA10 mutation (c.A265G; p.I89V) in GBM. IDH1-wildtype and PCDHGA10 mutation were significantly related to poor prognosis. IDH1 is an important biomarker in gliomas, whereas PCDHGA10 mutation has not been reported to correlate with gliomas. Different copy number variations (CNVs) and oncogenic signaling pathways were identified between LGG and GBM. Differential genomic landscapes between LGG and GBM were revealed in the Chinese population, and PCDHGA10, for the first time, was identified as the prognostic factor of gliomas. Our results might provide a basis for molecular classification and identification of diagnostic biomarkers and even potential therapeutic targets for gliomas.

Ensemble learning prediction framework for EGFR amplification status of glioma based on terahertz spectral features

Epidermal growth factor receptor (EGFR) plays a pivotal role in the initiation and progression of gliomas. In particular, in glioblastoma, EGFR amplification emerges as a catalyst for invasion, proliferation, and resistance to radiotherapy and chemotherapy. Current approaches are not capable of providing rapid diagnostic results of molecular pathology. In this study, we propose a terahertz spectroscopic approach for predicting the EGFR amplification status of gliomas for the first time. A machine learning model was constructed using the terahertz response of the measured glioma tissues, including the absorption coefficient, refractive index, and dielectric loss tangent. The novelty of our model is the integration of three classical base classifiers, i.e., support vector machine, random forest, and extreme gradient boosting. The ensemble learning method combines the advantages of various base classifiers, this model has more generalization ability. The effectiveness of the proposed method was validated by applying an individual test set. The optimal performance of the integrated algorithm was verified with an area under the curve (AUC) maximum of 85.8 %. This signifies a significant stride toward more effective and rapid diagnostic tools for guiding postoperative therapy in gliomas.

Comprehensive Molecular Genetic Analysis in Glioma Patients by Next Generation Sequencing

BACKGROUND

Glioma is caused by multiple genomic alterations. The evolving classification of gliomas emphasizes the significance of molecular testing. Next generation sequencing (NGS) offers the assessment of parallel combinations of multiple genetic alterations and identifying actionable mutations that guide treatment. This study comprehensively analyzed glioma patients using multi-gene NGS panels, providing powerful insights to inform diagnostic classification and targeted therapies.

METHODS

We conducted a targeted panel-based NGS analysis on formalin-fixed and paraffin-embedded nucleic acids extracted from a total of 147 glioma patients. These samples underwent amplicon capture-based library preparation and sequenced using the Oncomine Comprehensive Assay platform. The resulting sequencing data were then analyzed using the bioinformatics tools.

RESULTS

A total of 301 mutations, were found in 132 out of 147 tumors (89.8%). These mutations were in 68 different genes. In 62 tumor samples (42.2%), copy number variations (CNVs) with gene amplifications occurred in 25 genes. Moreover, 25 tumor samples (17.0%) showed gene fusions in 6 genes and intragenic deletion in a gene. Our analysis identified actionable targets in several genes, including 11 with mutations, 8 with CNVs, and 3 with gene fusions and intragenic deletion. These findings could impact FDA-approved therapies, NCCN guideline-based treatments, and clinical trials.

CONCLUSION

We analyzed precisely diagnosing the classification of gliomas, detailing the frequency and co-occurrence of genetic alterations and identifying genetic alterations with potential therapeutic targets by NGS-based molecular analysis. The high-throughput NGS analysis is an efficient and powerful tool to comprehensively support molecular testing in neurooncology.

Characteristics of glioblastomas and immune microenvironment in a Chinese family with Lynch syndrome and concurrent porokeratosis

Background

Lynch syndrome (LS)-associated glioblastoma (GBM) is rare in clinical practice, and simultaneous occurrence with cutaneous porokeratosis is even rarer. In this study, we analyzed the clinicopathological and genetic characteristics of LS-associated GBMs and concurrent porokeratosis, as well as evaluated the tumor immune microenvironment (TIME) of LS-associated GBMs.

Methods

Immunohistochemical staining was used to confirm the histopathological diagnosis, assess MMR and PD-1/PD-L1 status, and identify immune cell subsets. FISH was used to detect amplification of EGFR and PDGFRA, and deletion of 1p/19q and CDKN2A. Targeted NGS assay analyzed somatic variants, MSI, and TMB status, while whole-exome sequencing and Sanger sequencing were carried out to analyze the germline mutations.

Results

In the LS family, three members (I:1, II:1 and II:4) were affected by GBM. GBMs with loss of MSH2 and MSH6 expression displayed giant and multinucleated bizarre cells, along with mutations in ARID1A, TP53, ATM, and NF1 genes. All GBMs had TMB-H but not MSI-H. CD8+ T cells and CD163+ macrophages were abundant in each GBM tissue. The primary and recurrent GBMs of II:1 showed mesenchymal characteristics with high PD-L1 expression. The family members harbored a novel heterozygous germline mutation in MSH2 and FDPS genes, confirming the diagnosis of LS and disseminated superficial actinic porokeratosis.

Conclusion

LS-associated GBM exhibits heterogeneity in clinicopathologic and molecular genetic features, as well as a suppressive TIME. The presence of MMR deficiency and TMB-H may serve as predictive factors for the response to immune checkpoint inhibitor therapy in GBMs. The identification of LS-associated GBM can provide significant benefits to both patients and their family members, including accurate diagnosis, genetic counseling, and appropriate screening or surveillance protocols. Our study serves as a reminder to clinicians and pathologists to consider the possibility of concurrent genetic syndromes in individuals or families.

Molecular profile and clinical features of patients with gliomas using a broad targeted next generation-sequencing panel

Gliomas are the most common malignant primary brain tumors characterized by poor prognosis. The genotyping of tumors using next generation sequencing (NGS) platforms enables the identification of genetic alterations that constitute diagnostic, prognostic and predictive biomarkers. The present study investigated the molecular profile of 32 tumor samples from 32 patients with high-grade gliomas by implementing a broad 80-gene targeted NGS panel while reporting their clinicopathological characteristics and outcomes. Subsequently, 14 of 32 tumor specimens were also genotyped using a 55-gene NGS panel to validate the diagnostic accuracy and clinical utility of the extended panel. The median follow-up was 19.2 months. In total, 129 genetic alterations including 33 structural variants were identified in 38 distinct genes. Among 96 variants (single nucleotide variants and insertions and deletions), 38 were pathogenic and 58 variants of unknown clinical significance. TP53 was the most frequently mutated gene, followed by PTEN and IDH1 genes. Glioma patients with IDH1 mutant tumors were younger and had significantly longer overall survival compared to patients with wild-type IDH1 tumors. Similarly, tumors with TP53 mutations were more likely observed in younger patients with glioma. Subsequently, a comparison of mutational profiles of samples analyzed by both panels was also performed. Implementation of the comprehensive pan-cancer and the MOL panels resulted in the identification of 37 and 15 variants, respectively. Of those, 13 were common. Comprehensive pan-cancer panel identified 24 additional variants, 22 of which were located in regions that were not targeted by the MOL panel. By contrast, the MOL panel identified two additional variants. Overall, the present study demonstrated that using an extended tumor profile assay instead of a glioma-specific tumor profile panel identified additional genetic changes that may be taken into consideration as potential therapeutic targets for glioma diagnosis and molecular classification.

Epidemiological characteristics and genetic alterations in adult diffuse glioma in East Asian populations

Understanding the racial specificities of diseases-such as adult diffuse glioma, the most common primary malignant tumor of the central nervous system-is a critical step toward precision medicine. Here, we comprehensively review studies of gliomas in East Asian populations and other ancestry groups to clarify the racial differences in terms of epidemiology and genomic characteristics. Overall, we observed a lower glioma incidence in East Asians than in Whites; notably, patients with glioblastoma had significantly younger ages of onset and longer overall survival than the Whites. Multiple genome-wide association studies of various cohorts have revealed single nucleotide polymorphisms associated with overall and subtype-specific glioma susceptibility. Notably, only 3 risk loci-5p15.33, 11q23.3, and 20q13.33-were shared between patients with East Asian and White ancestry, whereas other loci predominated only in particular populations. For instance, risk loci 12p11.23, 15q15-21.1, and 19p13.12 were reported in East Asians, whereas risk loci 8q24.21, 1p31.3, and 1q32.1 were reported in studies in White patients. Although the somatic mutational profiles of gliomas between East Asians and non-East Asians were broadly consistent, a lower incidence of EGFR amplification in glioblastoma and a higher incidence of 1p19q-IDH-TERT triple-negative low-grade glioma were observed in East Asian cohorts. By summarizing large-scale disease surveillance, germline, and somatic genomic studies, this review reveals the unique characteristics of adult diffuse glioma among East Asians, to guide clinical management and policy design focused on patients with East Asian ancestry.

Deciphering cell-cell interactions and communication in the tumor microenvironment and unraveling intratumoral genetic heterogeneity via single-cell genomic sequencing

A tumor's heterogeneity has important implications in terms of its clonal origin, progression, stemness, and drug resistance. Therefore, because of its significance in treatment, it is important to understand the gene expression pattern of a single cell, track gene expression or mutation in heterogeneous cells, evaluate the clonal origin of cancer cells, and determine the selective evolution of different subpopulations of cancer cells. Researchers are able to trace a cell's mutation and identify different types of tumor cells by measuring the whole transcriptome with single-cell sequencing (scRNA-seq). This technology provides a better understanding of the molecular mechanisms driving tumor growth than that offered by traditional RNA sequencing methods. In addition, it has revealed changes in the mutations and functions of somatic cells as a tumor evolves; it has also clarified immune cell infiltration and activation. Research on scRNA-seq technology has recently advanced significantly, suggesting new strategies for the treatment of cancer. In short, cancer researchers have become increasingly dependent on scRNA-seq. This paper reviews the development, detection principles, and processes of scRNA-seq technology and their application in tumor research. It also considers potential clinical applications.

Detection of TERT Promoter Mutations as a Prognostic Biomarker in Gliomas: Methodology, Prospects, and Advances

This article reviews the existing approaches to determining the TERT promoter mutational status in patients with various tumoral diseases of the central nervous system. The operational characteristics of the most common methods and their transferability in medical practice for the selection or monitoring of personalized treatments based on the TERT status and other related molecular biomarkers in patients with the most common tumors, such as glioblastoma, oligodendroglioma, and astrocytoma, are compared. The inclusion of new molecular markers in the course of CNS clinical management requires their rapid and reliable assessment. Availability of molecular evaluation of gliomas facilitates timely decisions regarding patient follow-up with the selection of the most appropriate treatment protocols. Significant progress in the inclusion of molecular biomarkers for their subsequent clinical application has been made since 2016 when the WHO CNS classification first used molecular markers to classify gliomas. In this review, we consider the methodological approaches used to determine mutations in the promoter region of the TERT gene in tumors of the central nervous system. In addition to classical molecular genetical methods, other methods for determining TERT mutations based on mass spectrometry, magnetic resonance imaging, next-generation sequencing, and nanopore sequencing are reviewed with an assessment of advantages and disadvantages. Beyond that, noninvasive diagnostic methods based on the determination of the mutational status of the TERT promoter are discussed.